The scope of my personal project shrunk as the data came in and the days went by.
In the end, after many iterations in IPython, I got to fit a number of multilinear regression models with statsmodels, using
sklearn for model evaluation (root-mean-squared error), and the inevitable pyplot for visualization.

On Friday, the whole class delivered their presentations. My first-ever Keynote presentation was for a ficticious investor known by the name of Dino Brangelino. My conclusion: knowing the box office revenue of the opening weekend -on top of the production budget- reduces total revenue prediction error by 15%.